Software Quality assurance is critical to unlocking the real value of your investment in software infrastructure. You may spend a fortune to install and implement the world’s best software, but if it doesn’t function as desired, your investment may not yield the desired results. Software Quality Assurance is one of the key areas of focus for any organization using software as a part of their IT setup or those who are about to deploy new apps or platforms. To ensure their software performs the way it is meant to – whether on-premise or on the cloud, organizations need to partner with a reputed automation testing company.
Test automation is the practice of executing tests automatically, managing test data, and using results to enhance software quality and productivity. It’s a measure for assuring the quality of the software. However, it requires the involvement of the entire software development team, and users across various departments.
A test needs to meet certain conditions in order to be automated else it might not yield the desired results. One of the primary objectives of leveraging automation testing services is to save time, effort, and money. We have enlisted some general criteria for test automation. These may differ depending on the needs of your business and the use cases.
Naturally, a test must be repeatable. There is no point automating a test that can be run only once. Typically, a repeatable test consists of the following three steps:
You want to run the test in a consistent state. This means, once the QA Automation Testing is complete, the test environment should be restored to its original state.
A determinant function is akin to consistency. It implies that if a test is fed the same input, then the outcome will be the same every time. Consistency is key to establishing stability and robustness of the software. The same can be said for tests that can be automated.
Enterprise software typically works with a significantly high number of variable inputs that it’s not possible to have the same result over time. In fact, some variables may even be random, which can make it all the more challenging to determine the specific outcome.
Listed below are some of the many tests that can be automated:
There are many different types of code analysis tools available in the market today, including static and dynamic analysis tools. These tests may look for security flaws, or style and form. These tests run as soon as the new code is checked in. Testers can configure rules and keep the tools up to date before automating these tests.
Unit tests are used to test a single function, or unit of operation in isolation. These tests don’t depend on databases or external APIs. They are fast and are designed to test just the code only and not any external dependency.
A smoke test is a basic test that’s usually performed after an alpha deployment or during a maintenance procedure. The objective of a smoke test is to ensure that all services are up and running. It’s not a functional test. It can be run as part of an automated deployment or activated with a manual step.
Automated regression testing ensures apps still function as they should after they have been updated with new features, functions or fixes.
Integration tests pose an altogether new challenge. Integration tests, as the name indicates, needs to interact with external dependencies, and therefore they are more complicated to set up. Often, testing teams create virtual external resources, especially when they have to deal with resources beyond their control. For example, if you have a logistics app that interacts with a third-party web service, your test may fail unexpectedly if the web service is down. That does not necessarily mean that there’s a bug in your software. You should have enough flexibility to regulate the test environment to create each scenario virtually while staying clear of all the dependencies on external factors for determining the efficacy of your software.
Performance tests can be of many types, but they are all designed to test some aspect of a software’s performance. How does it hold up against extreme pressure? Are we testing the response times on high loads? Is the software scalable?
Sometimes these tests require simulating a huge number of users and/or transactions. In such a case, it’s important to have a test environment that can handle such requests.